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At least 433 records · Page 24

Pilot interaction with automated airborne decision making systems

Two project areas were pursued: the intelligent cockpit and human problem solving. The first area involves an investigation of the use of advanced software engineering methods to aid aircraft crews in procedure selection and execution. The second area is focused on human problem solving in dynamic environments, particulary in terms of identification of rule-based models land alternative approaches to training and aiding. Progress in each area is discussed.

Rouse, W. B.↗

Application of a periodic lattice filter for identifying a flexible structure

Lattice filters have properties which make them attractive for the application to the identification of the parameters of flexible structures. Here, the problem of both order and parameter estimation is addressed, where the numerical difficulties of an embedded lattice filter are avoided by applying a periodic lattice filter. With this formulation, it is quite natural to estimate system order by applying Akaike's (1976) information criterion to each channel of the periodic lattice filter. Several examples including nonstationary cases are simulated to demonstrate these facts.

Lee, Young Jae↗

Laser Remote Sensing of Pollution on Water Surfaces

One of the most important problems of modern environmental science is the detection and identification of various impurities in the ocean. Sources of impurities in sea water are diverse. The most common of them are accidental transport, agricultural, and oil industry spills. Once the ecological balance is disturbed, biological processes in sea water become affected, resulting in changes in chlorophyll concentrations, water turbidity, and temperature. During the last few years, we have created new types of lidars and arranged nearly ten aircraft and shipboard expeditions. Some aircraft expeditions dealt with terrestrial investigations. Others were devoted to oceanological research, the results of which are discussed here. Emphasis is on the detection of phytoplankton chlorophyll and hydrocarbon in sea water.

Bunkin, A. F.↗

Reducing the complexity of software systems - A strategic software perspective

The results of a combined management and technical initiative aimed at reducing the size and complexity associated with developing operations planning, scheduling, and resource management software systems are presented. The initiative has produced operations concepts, functional requirements, system architectures, a comprehensive lexicon, and software tools to revolutionize the traditional software technology and development practices for planning, scheduling, and resource management systems used in space operations control centers. Examples of technology and practices to reduce complexity include a method for projecting design consequences from an operations concept, a universal architecture for heuristic algorithms, an object-oriented framework for describing large classes of problems that parametrically adapt to all domain peculiarities, the identification of general approaches which respond to changes with minimum impact on systems implementations, and a management structure for prototyping to minimize the risks of ill-conceived designs.

Hornstein, Rhoda S.↗

NASA's Accident Precursor Analysis Process and the International Space Station

This viewgraph presentation reviews the implementation of Accident Precursor Analysis (APA), as well as the evaluation of In-Flight Investigations (IFI) and Problem Reporting and Corrective Action (PRACA) data for the identification of unrecognized accident potentials on the International Space Station.

Groen, Frank↗

Functional Autonomy Challenges in Sampling for an Europa Lander Mission

We present a baseline approach to Functional Autonomyfor the purpose of conducting excavation and samplingbehaviors in a proposed Europa Lander mission. Aspects ofthe problems of site selection, excavation progress tracking,and fault identification are related; with particular emphasison parameters peculiar to an icy moon environment. Firstpass approaches to addressing these challenges are presentedin isolation, while motivating the current development goal ofproducing a general Functional Autonomy architecture thatallows state estimation, fault diagnosis, isolation, & recovery(FDIR), and adaptive behaviors to be formulated in concert.

Backes, Paul↗

Proceedings of the Second Airborne Imaging Spectrometer Data Analysis Workshop

The Second Airborne Imaging Spectrometer (AIS) Data Analysis Workshop was held at the Jet Propulsion Laboratory on May 6, 7, and 8, 1986. It was attended by 100 people from seven countries. Papers were presented by 24 attendees; summaries of 19 of the papers are published in these Workshop Proceedings. The Second Workshop was divided into three sessions: Calibration, the Atmosphere, and Data Techniques; Geological Research; and Botanical and Geobotanical Research. Because many of the AIS researchers have had an additional year to work with their data, a general advance was seen in the utilization of the data for solving earth science problems. The major conclusions that can be drawn from the Workshop are: (1) Almost everyone now working with AIS data is attempting to take into account in data analysis the effects of the atmosphere and sensor calibration and performance. As a result, information extraction techniques are becoming more sophisticated and effective. (2) The emphasis on work in the geological disciplines is beginning to shift to the application of AIS data for solving geological problems now that the efficacy of the data for mineral identification has been demonstrated. (3) In the botanical sciences, interpretation of AIS data is becoming more quantitative. Several statistical techniques are under development for extracting the subtle differences in plant spectra in the region of the near infrared and short wavelength infrared. In summary, an overall advance was seen in the ability to effectively utilize the fundamentally new class of data acquired with imaging spectrometers. There was also a general feeling at the Workshop however, that much work remains to be done in remote sensing research before the maximum potential of these data for solving earth science problems is realized.

Gregg Vane↗

Identification of differences between finite element analysis and experimental vibration data

An important problem that has emerged from combined analytical/experimental investigations is the task of identifying and quantifying the differences between results predicted by F.E. analysis and results obtained from experiment. The objective of this study is to extend and evaluate the procedure developed by Sidhu for correlation of linear F.E. and modal test data to include structures with viscous damping. The desirability of developing this procedure is that the differences are identified in terms of physical mass, damping, and stiffness parameters instead of in terms of frequencies and modes shapes. Since the differences are computed in terms of physical parameters, locations of modeling problems can be directly identified in the F.E. model. From simulated data it was determined that the accuracy of the computed differences increases as the number of experimentally measured modes included in the calculations is increased. When the number of experimental modes is at least equal to the number of translational degrees of freedom in the F.E. model both the location and magnitude of the differences can be computed very accurately. When the number of modes is less than this amount the location of the differences may be determined even though their magnitudes will be under estimated.

Lawrence, C.↗

Identification of differences between finite element analysis and experimental vibration data

An important problem that has emerged from combined analytical/experimental investigations is the task of identifying and quantifying the differences between results predicted by F.E. analysis and results obtained from experiment. The objective of this study is to extend and evaluate the procedure developed by Sidhu for correlation of linear F.E. and modal test data to include structures with viscous damping. The desirability of developing this procedure is that the differences are identified in terms of physical mass, damping, and stiffness parameters instead of in terms of frequencies and modes shapes. Since the differences are computed in terms of physical parameters, locations of modeling problems can be directly identified in the F.E. model. From simulated data it was determined that the accuracy of the computed differences increases as the number of experimentally measured modes included in the calculations is increased. When the number of experimental modes is at least equal to the number of translational degrees of freedom in the F.E. model both the location and magnitude of the differences can be computed very accurately. When the number of modes is less than this amount the location of the differences may be determined even though their magnitudes will be underestimated.

Lawrence, Charles↗

A uniqueness result concerning the identification of a collection of cracks from finitely many electrostatic boundary measurements

The problem of locating and identifying a collection of finitely many cracks inside a planar domain from measurements of the electrostatic boundary potentials induced by specified current fluxes is considered. It is shown that a collection of n or fewer cracks can be uniquely identified by measuring the boundary potentials induced by n + 1 specified current fluxes, consisting entirely of electrode pairs.

Bryan, Kurt↗

On the identification of a harmonic force on a viscoelastic plate from response data

The problem of determining the force acting on a structure from measurements of the response of the structure to the force is an inverse problem. Presented is a method for determining the location, magnitude, and phase of a harmonic point force acting on a simply-supported classical viscoelastic rectangular plate from a number of displacement readings at discrete points on the plate. Presented also is a demonstration of the robustness of the solution technique to the effects of measurement noise as well as a means by which problems involving more general structural and loading configurations may be solved.

D'Cruz, J.↗

Parallel processing for digital picture comparison

In picture processing an important problem is to identify two digital pictures of the same scene taken under different lighting conditions. This kind of problem can be found in remote sensing, satellite signal processing and the related areas. The identification can be done by transforming the gray levels so that the gray level histograms of the two pictures are closely matched. The transformation problem can be solved by using the packing method. Researchers propose a VLSI architecture consisting of m x n processing elements with extensive parallel and pipelining computation capabilities to speed up the transformation with the time complexity 0(max(m,n)), where m and n are the numbers of the gray levels of the input picture and the reference picture respectively. If using uniprocessor and a dynamic programming algorithm, the time complexity will be 0(m(3)xn). The algorithm partition problem, as an important issue in VLSI design, is discussed. Verification of the proposed architecture is also given.

Cheng, H. D.↗

Scalable Approaches to Selecting Key Entities in Large Networked Infrastructure Systems

This work aims at bringing advances in discrete optimization algorithms to solving practical engineering problems at scale. Often times, in many engineering design problems, there is a need to select a small set of influential or representative elements from a large ground set of entities in an optimal fashion. Submodular optimization provides for a formal way to solve such problems. Common examples with infrastructure systems involve sensor placement and identification of key entities with certain objectives. However, scaling these approaches to large infrastructure systems can be challenging because of the high computational complexity of the overall framework that include the optimization algorithms as well as high-complexity compute-oracles that provide the necessary objective function values. In this work, we explore a well-studied and widely-applicable paradigm, namely leader-selection in a multi-agent networked setting in the context of scalable methodologies. We demonstrate novel frameworks that utilize variations of accelerated submodular optimization algorithms along with linear-algebraic methods that can help accelerate the oracle computations. We further explore this combination in conjunction with graph partitioning paradigms to take advantage of the accelerated algorithms in a distributed setting. Finally we demonstrate the key findings on a practical problem in an operational setting. For this, we leverage an example road network with approximately 18k nodes and 27k edges in a traffic control application, where we seek a limited number of k=200 key intersections. This problem can be solved in a serial setting in just under 5 hours providing more than 2 orders of magnitude speed-up over methods that do not consider acceleration techniques.

Visweswara Sathanur, Arun↗

Apollo experience report: Spacecraft relative motion and recontact analyses

Potential collision or accidental recontact problems between the spacecraft and other space vehicles (or components) existed during most of the Apollo missions. These problems were identified before each Apollo flight, and appropriate solutions for eliminating or minimizing the chance of collision were determined through relative motion analyses. A summary of the identification, solution, and analysis process for some of the more significant of these separation problems is presented. In addition, the scope of responsibility, the development of the study effort, and the computer simulation development, which supported the analysis process, are described.

Mcadams, R. E.↗

Bounded state space

This investigation is divided functionally into three different areas: (1) study of bounded state space, (2) nonlinear smoothing theory, and (3) system identification. (1) Study of bounded state space: necessary and sufficient conditions for an optimal control are obtained for a bounded state space optimal control problem. The difficulty of determining the so-called jump conditions is eliminated; however, the problem of determining the points where the response either enters or leaves the boundary still remains unsolved. (2) Nonlinear smoothing theory: nonlinear fixed-interval, fixed-point and fixed-lag smoothing of a random signal generated by a stochastic differential equation are investigated. Results on the asymptotic stability of a linear constant-parameter fixed-interval smoothing filter are obtained. (3) System identification: a particular stochastic modelling problem is solved. An Ito stochastic integral equation is used to mathematically model a black box having multiple inputs and multiple outputs. A new method for identifying system parameters is presented.

Eyman, E. D.↗

Pre-trained network-based transfer learning: A small-sample machine learning approach to nuclear power plant classification problem

Some research topics belonging to classification problems in the nuclear industry, such as fault diagnosis and accident identification, can be solved by feature extraction and subsequent application of statistical machine learning classifiers. Recently, deep neural network-based methods with automatic feature extraction and high accuracy have gained wide attention. They usually require large-scale training data, however, plant fault or accident data are scarce or difficult to obtain. Here this paper proposes a convolutional network (CNN)-based transfer learning method to solve this problem. The network's shallow layer is derived from a pre-trained CNN based on the ImageNet database to automatically extract features, and the deep layer is customized to match the classification problem. Data in non-image formats are converted to image formats and subsequently used to train the network. Case studies of rotating machines fault diagnosis show that the proposed method requires only limited training data to achieve high accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

Drake, R. L.↗

Extension and validation of a method for locating damaged members in large space trusses

The damage location approach employs the control system capabilities for the structure to test the structure and measure the dynamic response. The measurements are then used in a system identification algorithm to produce a model of the damaged structure. The model is compared to one for the undamaged structure to find regions of reduced stiffness which indicate the location of damage. Kabe's 3,4 stiffness matrix adjustment method was the central identification algorithm. The strength of his method is that, with minimal data, it preserves the representation of the physical connectivity of the structure in the resulting model of the damaged truss. However, extensive storage and computational effort were required as a result. Extension of the damage location method to overcome these problems is the first part of the current work. The central system identification algorithm is replaced with the MSMT method of stiffness matrix adjustment which was previously derived by generalizing an optimal-update secant method form quasi-Newton approaches for nonlinear optimization. Validation of the extended damage location method is the second goal.

Smith, Suzanne Weaver↗